Calculate derivatives of marginal effects for binary variables.
Calculates derivatives of marginal effects with respect to the estimated parameters for binary variables. Required to calculate standard errors of marginal effects.
D_discrete.margin_meanonly.mean(whichVars, whichXest, X, fouretas, link, std.dev)
D_discrete.margin_mean.var(whichZest, Z, fouretas, link, std.dev, gstd.dev)
D_discrete.margin_mean.alpha(estThresh, outcomematrix, fouretas, std.dev, link)
D_discrete.margin_var.mean(whichXest, X, fouretas, link, StdDevs)
D_discrete.margin_varonly.var(whichVars, whichZest, Z,fouretas, ZDinputs, link,
StdDevs, gsdmodel)
D_discrete.margin_var.alpha(estThresh, outcomematrix, fouretas, StdDevs, link)
D_discrete.margin_meanvar.mean(whichXest, X, BothEqLocs, fouretas, StdDevs, link)
D_discrete.margin_meanvar.var(whichZest, Z, BothEqLocs, fouretas, ZDinputs, link,
StdDevs,gsdmodel)whichVars |
Numeric vector stating indexes of variables that are binary and marginal effects are desired. |
whichXest |
Logical vector indicating the variables in X for which the relevant parameters were estimated. |
X |
Data matrix containing variables in mean equation. |
fouretas |
Inputs to link functions. |
link |
specifies the link function for the estimated model. |
std.dev |
The calculated standard deviation of the error terms. |
Z |
Data matrix containing variables in variance equation. |
whichZest |
Logical vector indicating the variables in Z for which the relevant parameters were estimated. |
gstd.dev |
The calculated derivative of the standard deviation of the error terms. |
estThresh |
Logical vector indicating which threshold parameters were estimated. |
outcomematrix |
A matrix that indicates the outcome variable. |
ZDinputs |
Values of inputs to function that gives standard deviation when binary variable is equal to 0 and 1. |
StdDevs |
Values of standard deviation when binary variable is equal to 0 and 1. |
gsdmodel |
Expression used to calculate derivative of standard deviation. |
BothEqLocs |
Dataframe describing locations of binary variables that are in both the mean and variance equations. |
Numeric matrix of derivatives of marginal effects with respect to estimated parameters.
Nathan Carroll, nathan.carroll@ur.de
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.